Toward Leveraging Pre-Trained Self-Supervised Frontends for Automatic Singing Voice Understanding Tasks: Three Case Studies
Author:
Affiliation:
1. University of Tsukuba,Tsukuba,Japan
Funder
National Taiwan University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10317071/10317095/10317286.pdf?arnumber=10317286
Reference60 articles.
1. WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
2. End-to-end lyrics transcription informed by pitch and onset estimation;deng;The 23rd International Society for Music Information Retrieval Conference (ISMIR),2022
3. HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
4. A Phoneme-Informed Neural Network Model For Note-Level Singing Transcription
5. Map-music2vec: A simple and effective baseline for self-supervised music audio representation learning;li,2022
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